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The MLPMEA 2019 special session provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Machine Learning for developing predictive models for different engineering applications. Machine Learning models are efficient for handing complex prediction models due to their outstanding
performance in handling large scale data sets with uniform characteristics and noisy data. Examples of MLPMEA 2019 topics of interest include building predictive models using Machine Learning to solve specific engineering problems such as regression and classification problems.
The aim of this work is to obtain a good perspective into the current state of practice of Machine Learning to address various predictive problems. Some topics relevant to this session include, but are not limited to:
Biomedical image analysis/processing
Clustering
Decision Support
Support Vector Machine
Time Series
Decision Trees
Fuzzy Logic & Systems
Probabilistic Reasoning
Lazy Learning
Classification
Recommender Systems
Expert Systems
Artificial Neural Networks
Evolutionary Algorithms
Ranking Algorithms
Cognitive Processes
Evolutionary Computing
Swarm Intelligence
Artificial Immune Systems
Markov Model
Chaos Theory
Multi-Valued Logic
Ensemble Techniques
Hybrid Intelligent Models
Reasoning Models
Applied to
Nuclear Engineering
Sustainable and Renewable Energy
Software Engineering
Biomedical Engineering
Mechanical Engineering
Civil Engineering
Electrical Engineering
Computer Engineering
Chemical Engineering
Industrial Engineering
Environmental Engineering
Papers should be submitted for this special session at the regular paper submission website (http://www.icmla-conference.org/icmla19/). Papers should not exceed a maximum of 6 pages (including abstract, body, tables, figures, and references), and should be submitted as a pdf in 2-column IEEE format. Detailed instructions for submitting the papers are provided on the conference at home page.
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